Neural Networks: Perceptron

This lecture introduces the main concepts behind neural networks, from their goal to mimic the brain's computation to the structure of biological neurons. It covers the Leaky-Integrator Neuron model, the Perceptron, activation functions, and the Perceptron training algorithm. The lecture also discusses the effect of noise on generalization and the implementation of multi-class classifiers.